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The Torch-MLIR project aims to provide first class support from the PyTorch ecosystem to the MLIR ecosystem.
Representation and Reference Lowering of ONNX Models in MLIR Compiler Infrastructure
An MLIR-based compiler framework bridges DSLs (domain-specific languages) to DSAs (domain-specific architectures).
A Suite of Parallel Approaches for Inference of Diffusion Transformer Models on GPU Clusters
Hunyuan-DiT : A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding
🚀 Kick-start your C++! A template for modern C++ projects using CMake, CI, code coverage, clang-format, reproducible dependency management and much more.
[GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction". An *ultra-simple, user-friendly …
LightLLM is a Python-based LLM (Large Language Model) inference and serving framework, notable for its lightweight design, easy scalability, and high-speed performance.
Open-Sora: Democratizing Efficient Video Production for All
AISystem 主要是指AI系统，包括AI芯片、AI编译器、AI推理和训练框架等AI全栈底层技术
Curated list of project-based tutorials
①[ICLR2024 Spotlight] (GPT-4V/Gemini-Pro/Qwen-VL-Plus+16 OS MLLMs) A benchmark for multi-modality LLMs (MLLMs) on low-level vision and visual quality assessment.
A high-throughput and memory-efficient inference and serving engine for LLMs
AAAI 2024: Visual Instruction Generation and Correction
Meta-Transformer for Unified Multimodal Learning
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
SVIT: Scaling up Visual Instruction Tuning
A Gradio web UI for Large Language Models.
Open-source and strong foundation image recognition models.
✨✨Latest Advances on Multimodal Large Language Models
InternGPT (iGPT) is an open source demo platform where you can easily showcase your AI models. Now it supports DragGAN, ChatGPT, ImageBind, multimodal chat like GPT-4, SAM, interactive image editin…
A guidance language for controlling large language models.
Tips and tricks for working with Large Language Models like OpenAI's GPT-4.
Benchmarking large language models' complex reasoning ability with chain-of-thought prompting